Agentic AI empowers banks with smart tools for digital-age advantage
Source: Supplied. Sergio Barbosa, chief executive officer of FutureBank.
'Traditional automation relies on fixed rules which limit adaptability and intelligence. Agentic AI, by contrast, can dynamically determine the best next action based on context, available tools, and goals, making workflows smarter and more autonomous,' says Sergio Barbosa, chief executive officer of FutureBank.
For banks, the shift to agentic AI is not just a technological upgrade — it's a radical reimagining of how they operate, interact with customers, and create value in a rapidly changing digital economy.
And those benefits aren't theoretical — they're showing up where it matters most. One of the most immediate benefits of agentic AI is operational efficiency.
By automating complex, multi-step processes such as case management, reconciliation processes, deal-making, and liquidity management, agentic AI reduces the need for human intervention, speeds up workflows, and minimises errors.
This will allow banks to run using smaller, leaner teams giving large banks the same kind of agility currently enjoyed by their smaller, more nimble counterparts.
Barbosa says these efficiencies will translate directly into improved cost-to-income ratios, allowing banks to do more with less and remain competitive in an increasingly contested environment.
Empowering the customer
Furthermore, the promise of agentic AI extends far beyond internal operations. Barbosa sees a future where customers are empowered by their own AI agents, or digital representatives, that aggregate financial data, optimise spending, and even negotiate better deals on their behalf.
'This is going to flip things on their head. Customers will have access to their own personal AI, capable of aggregating data across all their accounts to enable personalised financial management — all within the safety of the bank's system,' he explains.
This shift from institution-centric to customer-centric AI marks a profound change in the relationship between banks and their clients, enabling hyper-personalised services and proactive, predictive financial management.
What's more, agentic AI's ability to leverage both private and public data, combined with advanced techniques like using vector databases, Retrieval/ Cache Augmented Generation (RAG/CAG) and Model Context Protocol (MCP) servers, allows for context-aware, forward-looking insights. Customers can move from reactive problem-solving (responding to issues as they arise), to proactive, strategic decision-making.
'Agentic AI continuously monitors customer accounts, transactions, and market conditions. It can proactively alert customers to potential risks and opportunities, before issues arise. This not only enhances the customer experience but also helps banks build deeper, more trusted relationships with their clients,' Barbosa says.
Stablecoin momentum builds
Barbosa sees a significant opportunity for banks at the intersection of agentic AI and crypto.
'Currency programmability opens up new possibilities for automating interbank relationships, deal-making, liquidity management, and treasury functions, which are all areas that are notoriously difficult to manage manually. With agentic AI, banks can leverage these programmable assets to streamline operations, enforce regulations more easily, and create new, efficient business models,' he shares.
Visa and Mastercard have both launched their agentic commerce and stablecoin plays with a Visa spokesperson painting a picture of consumers using AI agents to find, shop and buy products based on their pre-selected preferences.
Visa will also be able to offer stablecoin-linked Visa cards to customers in multiple countries. This would allow cardholders to make everyday purchases from a stablecoin balance at any merchant that accepts Visa.
Not a straightforward journey
The path to agentic AI is not without its challenges. Banks are traditionally accustomed to closed, highly regulated environments, and the shift to open protocols and transparent systems can be daunting.
Barbosa explains that legacy technology presents a significant hurdle, as integrating new AI capabilities with old systems often requires building interfaces and orchestration layers to connect the two worlds.
Security and fraud risks are also evolving, with open systems and programmable money introducing new attack vectors that demand advanced monitoring and prevention strategies.
While bullish about agentic AI, Research firm, Forrester, paints a realistic picture of the challenges for early adopters. 'We are still in the early stages of agentic AI's market impact; companies must test, learn, and iterate because these powerful systems can be misaligned, creating actions that are at best undesirable and at worst harmful to your customers and critical applications.'
However, Barbosa says that working with experienced partners can help de-risk the journey.
'By prioritising open APIs and standardised interfaces, such as MCP servers, we aim to make it easy for both internal and external agentic AI agents to securely interact with our platform. This will not only accelerate innovation but also foster a broader ecosystem of fintech partners and customer-owned AI solutions. We see agentic AI as the catalyst for a new era of banking which is defined by operational excellence."
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